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Fire ants (Solenopsis invicta) feeding on a honey bee larva. Photo by A. Payne. 

Fire ants (Solenopsis invicta) feeding on a honey bee larva. Photo by A. Payne. 

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Citations

... Through the utilization of AI, scientists can expedite the exploration, analysis, and utilization of honey bee peptides, propelling further understanding of bee biology, health, and ecological relationships [121][122][123]. Moreover, utilizing AI-driven approaches enhances traditional experimental methods by providing novel perspectives and predictive abilities for peptide-based research, not only in apiculture but also in agriculture and biomedicine [119,121,[124][125][126]. • Advanced techniques like generative adversarial networks (GANs) and reinforcement learning have revolutionized the field of structure prediction. ...
... These techniques allow for efficient and non-invasive analyses. [124,[154][155][156][157] ...
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Honey is a natural product that is used by a large number of people because of its distinctive compositional constituents, which have a considerable impact on its market value. The distinctive combination of amino acids and sugars found in honey’s composition, along with its peptide content, could potentially provide several benefits to human health. During the past few years, cutting- edge techniques have been developed and used for the purpose of investigating, identifying, and characterizing peptides that are produced from honey bees. Therefore, the purpose of this review is to examine current trends and technological advancements in the study of honey bee-derived peptides, focusing on innovative and cutting-edge methods. Furthermore, this review explores various attributes of honey and its components, including the honey bee-derived peptide defensin-1. In addition, this review investigates various methods for separating and purifying peptides, as well as the factors that affect these methods. Additionally, defensin-1, a peptide produced by honey bees, is discussed along with its antioxidant and antimicrobial capabilities. In addition, this review focuses on cutting-edge and innovative omic methods used to study honey bee peptides, as well as the significance of artificial intelligence tools in their investigation. Consequently, the review paper delves into various significant obstacles faced by researchers and scientists studying honey bee peptides, while also offering an extensive range of fascinating opportunities and possibilities for future research for those interested in groundbreaking discoveries in this area.